find_recent_changesReturn deduplicated changes from the dated pipeline delta artefacts.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter changes to one category; all categories by default. | |
| window_days | No | Number of days back to include registry changes. Default 7. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only, open-world, idempotent, and non-destructive behavior. The description adds value by disclosing that results are deduplicated and sourced from dated pipeline delta artefacts, which are behavioral details beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence with no filler. It is slightly jargon-heavy ('delta artefacts'), but every part earns its place and the core behavior is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a high-coverage schema, an output schema, and strong annotations, the description is largely sufficient. The main gap is not clarifying how 'deduplicated' applies or when the 'pipeline delta artefacts' are considered 'recent', but overall the definition enables correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already well documented in the schema. The description adds no additional meaning for 'category' or 'window_days', but it does not need to since the schema already explains them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Return'), a specific resource ('changes from the dated pipeline delta artefacts'), and a distinguishing behavior ('deduplicated'). This makes the tool's core purpose understandable, though it does not explicitly contrast it with sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus sibling tools like find_by_manufacturer or search_pharma. The description implies a use case around recent changes, but there are no explicit conditions, exclusions, or alternative routes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are largely distinct, with search_pharma focused on category-specific field search and find_by_manufacturer on manufacturer substring lookup, which could cause occasional confusion. get_npra_record, get_pharma_health, find_recent_changes, and verify_pharma_artifact each have clear, separate purposes.
All tool names use lowercase snake_case with a verb-led pattern, mostly following verb_noun conventions. The main deviation is find_by_manufacturer, which uses a prepositional phrase rather than a direct object, but overall naming is predictable and readable.
Six tools is a well-scoped set for a data retrieval and verification server, covering search, exact lookup, delta tracking, document retrieval, and artifact verification without redundancy or bloat.
The server provides strong coverage for discovery, retrieval, change tracking, and verification of pharma data, fitting its evident read-only role. Minor gaps include no explicit way to list all categories or combine filters across categories beyond the exact record lookup, but these are workarounds.